(1) Field of Invention
The present invention relates to a method for image registration and, more particularly, to a method for image registration which utilizes particle swarm optimization.
(2) Description of Related Art
Image registration is the process of transforming different sets of data into one coordinate system. For instance, two images of the same scene or set of objects are aligned, where the images may be from different cameras or different viewpoints. Registration is necessary in order to be able to compare or integrate the data obtained from different measurements.
Conventional approaches to image registration are presented by Zitova and Flusser (see Literature Reference No. 11). As described by the authors, current approaches rely on the following steps: selecting and finding a set of features from the candidate images to be registered; matching the features from one image to those of the other image; and estimating a transformation based on the set of matches. FIG. 1 illustrates the typical process of image registration which involves first selecting and detecting features 100 from a reference image 102 and a test image 104. Next, the features or regions are matched 106 between the images 102 and 104. A transform model is then estimated 108. Finally, one of the images 102 or 104 is transformed into the coordinates of the other image 102 or 104 to perform the image registration transformation 110. The result is a set of registered images 112.
Each of the steps above carries potential risks for the process to fail. For instance, features may be unreliable or may be difficult to find in one image or the other. Additionally, feature matching can fail and result in mismatches, which then results in errors in the estimated transformation. Finally, transformation parameter estimation can be complicated and error-prone when the transformation model is complicated, non-linear, or contains multiple parameters.
Therefore, a continuing need exists for an approach which significantly simplifies the image registration process and eliminates each of the disadvantages presented above.